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水中电子轨迹模拟:GPU、CPU与EUMED网格装置的性能比较

Electron tracks simulation in water: Performance comparison between GPU CPU and the EUMED grid installation.

作者信息

Seif Edgard, El Bitar Ziad, Incerti Sébastien, Bernal Mario A, Francis Ziad

机构信息

Saint Joseph University, UR Mathématiques et Modélisation, Beirut, Lebanon.

IPHC, UMR 7178-CNRS/IN2P3, Strasbourg, France.

出版信息

Phys Med. 2022 Dec;104:56-66. doi: 10.1016/j.ejmp.2022.10.020. Epub 2022 Nov 8.

Abstract

PURPOSE

We explored different technologies to minimize simulation time of the Monte-Carlo method for track generation following the Geant4-DNA processes for electrons in water.

METHODS

A GPU software tool is developed for electron track simulations. A similar CPU version is also developed using the same collision models. CPU simulations were carried out on a single user desktop computer and on the computing grid France Grilles using 10 and 100 computing nodes. Computing time results for CPU, GPU, and grid simulations are compared with those using Geant4-DNA processes.

RESULTS

The CPU simulations better performs when the number of electrons is less than 10 with 100 eV initial energy, this number decreases as the energy increases. The GPU simulations gives better results when the number of electrons is more than 10 with initial energy of 100 eV, this number decreases to 10 for electrons with 10KeV and increases back with higher energy. The use of the grid introduces an additional queuing time which slows down the overall simulation performance. Thus, the Grid gives better performance when the number of electrons is over 10 with initial energy of 10KeV, and this number decreases as the energy increases.

CONCLUSIONS

The CPU is best suited for small numbers of primary incident electrons. The GPU is best suited when the number of primary incident particles occupies sufficient resources on GPU card in order to get an important computing power. The grid is best suited for simulations with high number of primary incident electrons with high initial energy.

摘要

目的

我们探索了不同技术,以尽量减少蒙特卡罗方法在遵循水中电子的Geant4-DNA过程进行径迹生成时的模拟时间。

方法

开发了一种用于电子径迹模拟的GPU软件工具。还使用相同的碰撞模型开发了类似的CPU版本。CPU模拟在单用户台式计算机以及使用10和100个计算节点的法国网格计算网格上进行。将CPU、GPU和网格模拟的计算时间结果与使用Geant4-DNA过程的结果进行比较。

结果

当初始能量为100 eV时,电子数量少于10个时,CPU模拟表现更佳,随着能量增加,这个数量会减少。当初始能量为100 eV时,电子数量多于10个时,GPU模拟给出更好的结果,对于10 keV的电子,这个数量减少到10,随着能量更高又会增加。使用网格会引入额外的排队时间,从而减慢整体模拟性能。因此,当初始能量为10 keV且电子数量超过10个时,网格给出更好的性能,并且这个数量随着能量增加而减少。

结论

CPU最适合少量初级入射电子。当初级入射粒子数量在GPU卡上占用足够资源以获得强大计算能力时,GPU最适合。网格最适合具有高初始能量的大量初级入射电子的模拟。

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